class_docstr: Logging in tensorboard without tensorflow ops.
  
  Simple example on how to log scalars and images to tensorboard without tensor ops.
  License: Copyleft
  
  __author__ = "Michael Gygli"
docstr: Log a scalar variable.
  Parameter
  ----------
  tag : basestring
      Name of the scalar
  value
  step : int
      training iteration
docstr_tok: ["Log","a","scalar","variable",".","Parameter","--","--","--","--","--","tag",":","basestring","Name","of","the","scalar","value","step",":","int","training","iteration"]
code: def log_scalar(self, tag, value, step):
      """Log a scalar variable.
      Parameter
      ----------
      tag : basestring
          Name of the scalar
      value
      step : int
          training iteration
      """
      summary = tf.Summary(
          value=[tf.Summary.Value(tag=tag, simple_value=value)]
      )
      self.writer.add_summary(summary, step)
      self.writer.flush()
  
imports: import csv
  import numpy
  import tensorflow
  import os
  import six
label_desc: Use image node_id 2 for calling the Summary obj's underlying member method code with example usage: obj.log_scalar(tag, value, step) without return types